Jaroslav Budis, Marcel Kucharik, Frantisek Duris, Juraj Gazdarica, Michaela Zrubcova, Andrej Ficek, Tomas Szemes, Brona Brejova, Jan Radvanszky. Dante: genotyping of known complex and expanded short tandem repeats. Bioinformatics, 2018. Accepted for publication.
Download preprint: not available
Download from publisher: https://doi.org/10.1093/bioinformatics/bty791
Related web page: not available
Bibliography entry: BibTeX
Motivation: Short tandem repeats (STRs) are stretches of repetitive DNA in which short sequences, typically made of 2-6 nucleotides, are repeated several times. Since STRs have many important biological roles and also belong to the most polymorphic parts of the human genome, they became utilized in several molecular-genetic applications. Precise genotyping of STR alleles, therefore, was of high relevance during the last decades. Despite this, massively parallel sequencing (MPS) still lacks the analysis methods to fully utilize the information value of STRs in genome scale assays. Results: We propose an alignment-free algorithm, called Dante, for genotyping and characterization of STR alleles at user-specified known loci based on sequence reads originating from STR loci of interest. The method accounts for natural deviations from the expected sequence, such as variation in the repeat count, sequencing errors, ambiguous bases, and complex loci containing several different motifs. In addition, we implemented a correction for copy number defects caused by the polymerase induced stutter effect as well as a prediction of STR expansions that, according to the conventional view, cannot be fully captured by inherently short MPS reads. We tested Dante on simulated data sets and on data sets obtained by targeted sequencing of protein coding parts of thousands of selected clinically relevant genes. In both these data sets, Dante outperformed HipSTR and GATK genotyping tools. Furthermore, Dante was able to predict allele expansions in all tested clinical cases. Availability: Dante is open source software, freely available for download at https://github.com/jbudis/dante. Supplementary Information: Supplementary data are available at Bioinformatics online.